Will hunt-and-destroy algorithms get Apple?

Nigam Arora is an engineer, nuclear physicist, author, and entrepreneur and
the founder of two Inc. 500 fastest growing companies. He is also the developer
of the ZYX Change Method
to profit from change by investing. The premise is that most money is made by
predicting change before the crowd. Arora is the chief investment officer at
The Arora Report and the
editor of four newsletters that track the ZYX Change Method. Nigam can be
reached at Nigam@TheAroraReport.com.

In stock trading, twin practices have coexisted for ages. First, a large number of investors enter stop-loss orders to protect themselves. Second, such stop-loss orders become sitting ducks for some professionals.

In the past, it was a common complaint that market makers and brokers tended to run the stops. These days hunt-and-destroy algorithms have evolved to run down the stops. Such algorithms simply try to guess where the stops are grouped, and if stops are hit, the algorithms take advantage, first, by short-selling and then buying to cover. The complexities are overly simplified here to illustrate the point.

Apple Is vulnerable to stop running

Monday morning, Apple
AAPL, +1.72%
dipped to $497 in the premarket as both The Wall Street Journal and Japan's Nikkei reported that Apple had cut orders for screens and other parts for the iPhone 5. According to Nikkei, Apple has asked Japan Display, Inc., Sharp Corp, and LG Display to cut the orders for the iPhone 5 screens by about one half. According to the report Apple has also cut orders for other iPhone components.

This was a regurgitation of old news. Recently, a number of analysts have cut their targets and/or estimates on Apple based on supply-chain checks. Never mind that the news was old, and jittery investors pushed the stock below $500.

Also sold off were Apple component suppliers such as Cirrus Logic (CRUS), QUALCOMM (QCOM), Avago Technologies (AVGO), Broadcom (BRCM), TriQuint Semiconductor (TQNT), Skyworks Solutions (SWKS), and SanDisk (SNDK). Electronic assembly outfits such as Jabil Circuit (JBL) and Nam Tai Electronics (NTE), not known as major Apple vendors were sold off in sympathy.

As the day progressed, and Apple stock attempted to stage a mild recovery, telecommunication stocks including AT&T (T), Verizon (VZ) and Sprint (S) lagged.

The point is that Apple is vulnerable to further selling. If such selling takes place, stop running by hunt-and-destroy algorithms is highly likely.

Know where the stops are

The first step in protecting yourself is to know where the stops are congregating. For most investors, there is no legal way to know this with certainty. It is a guessing game.

Our 30 years of experience in the markets and extensive back-testing shows that the stops tend to congregate at five places:

Just below the last swing low. In the case of Apple, it would be below $497.

Round numbers. In the case of Apple it would be below $500.

Just below trendlines.

Just below crossover of certain moving averages.

Just below where sell signals would be generated by popular technical indicators.

How to protect yourself

We take precautions to make sure that our subscribers do not become victims of such algorithms. Further, as part of our tactics, we help our subscribers profit from buying into artificially depressed prices that occur from such algorithms.

The following are the elements of the ZYX Change Method Trade Management Guidelines:

Not placing stops in the zones where others can easily anticipate. In other words, do not becoming a sitting duck.

Not using stops as the primary risk-control mechanism.

Anticipating the stops would be run and exiting trading positions before such occurrences as well as reducing the size of long-term investment positions before such occurrences. Notice the distinction between trading positions and long-term investment positions.

Stepping up and buying when prices are artificially depressed because of stop-loss orders getting hit.

Having accumulated Apple at a lower price has positioned us to take advantage of hunt-and-destroy algorithms by buying at artificially depressed prices due to stop losses being hit.

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